Embedding capacity raising in reversible data hiding based on prediction of difference expansion

Most of the proposed methods of reversible data hiding based on difference expansion require location maps to recover cover images. Although the location map can be compressed by a lossless compression algorithm, this lowers embedding capacity and increases computational cost during the procedures of embedding and extracting. The study presents an adaptive reversible data scheme based on the prediction of difference expansion. Since each cover pixel generally resembles its surrounding pixels, most of the difference values between the cover pixels and their corresponding predictive pixels are small; therefore, the proposed scheme gains from embedding capacity by taking full advantage of the large quantities of smaller difference values where secret data can be embedded. The proposed scheme offers several advantages, namely, (1) the location map is no more required, (2) the embedding capacity can be adjusted depending on the practical applications, and (3) the high embedding capacity with minimal visual distortion can be achieved. Moreover, the experimental results demonstrate that the proposed scheme yields high embedding capacity by comparing the related schemes that are proposed recently.     

High capacity data hiding schemes for medical images based on difference expansion

Since the difference expansion (DE) technique was proposed, many researchers tried to, improve its performance in terms of hiding capacity and visual quality. In this paper, a new scheme, based on DE is proposed in order to increase the hiding capacity for medical images. One of the characteristics of medical images, among the other types of images, is the large smooth regions. Taking advantage of this characteristic, our scheme divides the image into two regions; smooth region and non-smooth region. For the smooth region, a high embedding capacity scheme is applied, while the original DE method is applied to the non-smooth region. Sixteen DICOM images of different modalities were used for testing the proposed schemes. The results showed that the proposed scheme has higher hiding capacity compared to the original schemes.     

Using quad smoothness to efficiently control capacity-distortion of reversible data hiding

One of the main uses of data hiding is to protect secret messages being transmitted on the Internet. Reversible data hiding can fully recover the original host image after extracting the secret message. It is especially suitable for applications where, after extracting the secret message, the quality of the recovered host image cannot be compromised, such as for medical or military image data.Many difference-expansion-based (DE-based) reversible data hiding methods have made use of a threshold value to control the stego-image's quality. Usually repeated trial and error is required to find a relatively good threshold with acceptable capacity-distortion behavior. This paper introduces a scheme that does not require a threshold value, such as is used in Alattar's quad-based reversible data hiding. It applies a prediction of quad of quads smoothness to determine the embedding sequence. The proposed scheme is shown to perform better than other DE-based schemes. Results showed that it has the ability of maintaining embedding quality at all capacity levels, especially when the embedding capacity is at low to medium levels.     

Prediction-based reversible data hiding

For some applications such as satellite and medical images, reversible data hiding is the best solution to provide copyright protection or authentication. Being reversible, the decoder can extract the hidden data and recover the original image without distortion. In this paper, a reversible data hiding scheme based on prediction error expansion is proposed. The predictive value is computed by using various predictors. The secret data is embedded in the cover image by exploiting the expansion of the difference between a pixel and its predictive value. Experimental results show that our method is capable of providing a great embedding capacity without making noticeable distortion. In addition, the proposed scheme is also applicable to various predictors.     

A reversible data hiding scheme using complementary embedding strategy

Obtaining good visual quality and high hiding capacity with reversible data hiding systems is a technically challenging problem. In this paper, we propose a simple reversible data hiding scheme that uses a complementary hiding strategy. The proposed method embeds one secret bit horizontally and vertically into one cover pixel of a grayscale cover image by decreasing odd-valued pixels and increasing even-valued pixels by one. Experimental results show that the hiding capacity measured by bit per pixel (bpp) of the proposed scheme is at least 1.21 bpp with a PSNR (peak signal-to-noise ratio) value greater than 52 dB for all standard test images. Especially in the case of four-layer embedding, the PSNR value of the proposed method is still greater than 51 dB at a hiding capacity of about 5 bpp for all standard test images. In addition, the proposed method is quite simple because it primarily uses additions and subtractions. These results indicate that the proposed scheme is superior to many existing reversible data hiding schemes introduced in the literature.     

A reversible data hiding scheme based on the Sudoku technique

Data hiding, also known as information hiding, plays an important role in information security for various purposes. Reversible data hiding is a technique that allows distortion-free recovery of both the cover image and the secret information. In this paper, we propose a new, reversible data hiding scheme that is based on the Sudoku technique and can achieve higher embedding capacity. The proposed scheme allows embedding more secret bits into a pair of pixels while guaranteeing the good quality of the stego-image. The experimental results showed that the proposed scheme obtained higher embedding capacity than some other previous schemes. In addition, our proposed scheme maintained the good visual quality of the stego-image (i.e., PSNR > 46 dB), which outperforms some existing schemes.     

基于改进像素排序预测的大容量可逆数据隐藏

基于像素排序的误差扩展方法能实现高保真度的可逆数据隐藏,但嵌入容量较小。针对这一问题,Qu等提出了以像素为单位的像素排序方法,即使用排序后的上下文像素来预测目标像素。尽管在嵌入容量上实现了较大突破,但Qu算法单一的嵌入策略不能充分利用平滑区域的数据冗余。考虑到以像素为单位的像素排序方法避免了嵌入像素定位问题,本文提出进一步划分目标像素,并相应地提出了新的基于方向编码的嵌入策略和两轮嵌入式的数据嵌入方案。平滑区域的目标像素预测准确率高,通过双向修改该类像素实施数据嵌入能使得嵌入容量增幅达50%,这意味着后续嵌入操作仅需更少量的非平滑区域目标像素,因此算法可以采用更小的区域复杂度阈值以提高预测准确率。实验结果表明本文工作不仅进一步稳固了Qu算法在嵌入容量上的优势,并且有利于提高嵌入图像保真度。与现有基于像素排序的误差扩展方法相比,本文算法在多数情况下能取得更优的嵌入图像保真度。     

A high stego-image quality steganographic scheme with reversibility and high payload using multiple embedding strategy

Tian’s method is a breakthrough reversible data embedding scheme with high embedding capacity measured by bits per pixel (bpp) and good visual quality measured by peak signal-to-noise ratio (PSNR). However, the embedding capacity and visual quality of this method can be significantly improved. Thus, we propose a simple reversible steganographic scheme in spatial domain for digital images by using the multiple embedding strategy. The proposed method horizontally and vertically embeds one secret bit into one cover pixel pair. The experimental results show that the proposed reversible steganographic method achieves good visual quality and high embedding capacity. Specifically, with the one-layer embedding, the proposed method can obtain the embedding capacity of more than 0.5 bpp and the PSNR value greater than 54 dB for all test images. Especially, with the five-layer embedding, the proposed method has the embedding capacity of more than 2 bpp and the PSNR value higher than 52 dB for all test images. Therefore, the proposed method surpasses many existing reversible data embedding methods in terms of visual quality and embedding capacity.     

Reversible data hiding of high payload using local edge sensing prediction

This paper tries to analyse a new framework in lossless data hiding research. Its key is how adaptively to get better difference image architectures for given applications. A unique sampled pattern is introduced and described in term of high-similar interpolation image. The proposed method updates a type of conventional algorithm, smoothly accesses to current reconstruction implementation, and outperforms solo weighing approach, particularly in the perceptual quality. Combinational weight factor can be adaptively adjusted by estimating interpolation errors around neighbor pixels. Seeking higher peak value in the difference-image is also our concerns. As an entire algorithm, reversible data hiding based on histogram-difference-shift is also reported. Simulations results demonstrate and verify that our approach is much effective than some recent methods with good generalization performance.     

An efficient image interpolation increasing payload in reversible data hiding

Image interpolation is a very important branch in image processing. It is widely used in imaging world, for example, image interpolation is often used in 3-D medical image to compensate for information insufficiency during image reconstruction by simulating additional images between two-dimensional images. Reversible data hiding has become significant branch in information hiding field. Reversibility allows the original media to be completely restored without any degradation after the embedded messages have been extracted. This study proposes a high-capacity image hiding scheme by exploiting an interpolating method called Interpolation by Neighboring Pixels (INP) on Maximum Difference Values to improve the performance of data hiding scheme proposed by Jung and Yoo. The proposed scheme offers the benefits of high embedding capacity with low computational complexity and good image quality. The experimental results showed that the proposed scheme has good performance for payload up to 2.28 bpp. Moreover, the INP yields higher PSNRs than other interpolating methods such as NMI, NNI and BI.     

A reversible watermarking scheme for two-dimensional CAD engineering graphics based on improved difference expansion

Difference expansion is widely used in reversible watermarking for raster images, but it cannot be applied to data with low correlation, due to its large distortion. In this paper, an improvement is made to difference expansion technology to make it suitable for two-dimensional (2D) computer-aided design (CAD) engineering graphics. Based on improved difference expansion (IDE), a reversible watermarking scheme for 2D CAD engineering graphics is proposed. First, all vertices of the 2D CAD engineering graphics are extracted, and then the relative coordinates of these vertices are calculated. Finally, the encrypted watermark is embedded into the scale factor of the relative coordinates by using IDE technology. Experimental results show that the proposed scheme has a large capacity, good imperceptibility, and is robust against operations such as transformation, rotation, and equal scaling.     

基于三分量预测误差差值扩展的可逆数据隐藏

针对传统差值扩展存在过分修改像素值、须嵌入定位图等缺陷,提出了一种新的彩色图像可逆数据隐藏算法。首先利用色彩分量之间的相关性减小差值,并根据扩展方向和差值的符号,用较小的差值扩展量修改部分色彩分量的像素值,扩展方向由可能产生上溢和下溢的像素数量决定;其次采用单向像素值调整的方法避免像素值溢出,并用少量的调整信息代替定位图,嵌入容量大幅提高;最后改进差值直方图平移技术控制嵌入容量和图像失真。提取端根据临界像素值的顺序定位调整的像素位置,用调整信息恢复调整的像素值,在提取信息的同时可无损地恢复原始图像。实验结果表明,所提出的算法在大幅提高嵌入容量的同时,仍能保持较高的图像质量。     

A local variance-controlled reversible data hiding method using prediction and histogram-shifting

The stego image quality produced by the histogram-shifting based reversible data hiding technique is high; however, it often suffers from lower embedding capacity compared to other types of reversible data hiding techniques. In 2009, Tsai et al. solved this problem by exploiting the similarity of neighboring pixels to construct a histogram of prediction errors; data embedding is done by shifting the error histogram. However, Tsai et al.’s method does not fully exploit the correlation of the neighboring pixels. In this paper, a set of basic pixels is employed to improve the prediction accuracy, thereby increasing the payload. To further improve the image quality, a threshold is used to select only low-variance blocks to join the embedding process. According to the experimental results, the proposed method provides a better or comparable stego image quality than Tsai et al.’s method and other existing reversible data hiding methods under the same payload.     

无定位图的预测误差差值扩展可逆数据隐藏*

将Tian差值扩展技术应用于彩色图像中,提出一种利用预测误差差值进行扩展嵌入的彩色图像可逆数据隐藏算法。针对传统差值扩展技术存在过分修改像素灰度值、须嵌入定位图等缺点,首先利用色彩分量间的相关性减小差值,并将差值扩展量分散到两个色彩分量中;其次,对直方图平移技术进行改进,使得同等嵌入率下图像质量达到最佳;最后由两个色彩分量中像素的预测值之和决定可用于扩展嵌入的像素,无须保存溢出定位图,提取端在提取信息时可无损地恢复原始图像。实验结果表明,与其他算法相比,该算法在同等嵌入率下可取得更好的图像质量,算法复杂度     

A new difference expansion transform in triplets for reversible data hiding

Difference expansion (DE) has been widely used for reversible data hiding. In this paper, a novel transform which embeds two bits of information in a triplet of coefficients is presented. This transform can be applied in spatial or frequency domains and induces minimum distortion to the initial data or coefficients. The proposed method outperforms all similar DE methods using triplets in terms of computational cost, visual quality and bitrate.     

利用差值扩展进行可逆数据隐藏的新算法

基于整数哈尔(Haar)小波变换,提出一种新的利用横向和纵向差值图像进行扩展嵌入的数据隐藏算法。传统的差值嵌入技术最大的缺点是在第二重嵌入开始之前图像的质量已经遭到破坏,原因是前一重嵌入用到了很大的差值。针对这个问题,该方法动态地把负载分配到两个正交方向上的图像进行嵌入。尽量使这两个方向上用于嵌入的差值属于同一个幅值范围。与其他算法相比,本算法在同等嵌入率下可取得更好的图像质量。     

A reversible data hiding scheme based on graph neighbourhood degree

Abstract

The perceptibility and capacity are two vital criteria of data hiding scheme. Concerning these criteria, data hiding algorithm used images as cover object based on the graph theory is proposed in this study. Images are quantised according to determined range and then quantised images are divided into n × n sized blocks. Each block is accepted as a graph and vertexes which have the same quantisation value are accepted as neighbours. Neighbourhood degrees of vertexes are calculated and indices of vertexes that have a neighbourhood degree over the threshold value are stored in the codebook. Pixel values indicated by these indices in the codebook are used for data hiding process. In this algorithm, there is no need for edge extraction because of hiding data to pixels containing vertexes having high neighbourhood degrees. The proposed method is compared with similar methods in literature in terms of the perceptibility and capacity. More successful results are provided than the others.     

Improved PVO-based reversible data hiding

This work extends a recently proposed reversible data hiding (RDH) scheme of Li et al. which is based on pixel-value-ordering and prediction-error expansion. In Li et al.ʼs method, the maximum and minimum of a pixel block are predicted and modified to embed data. The pixel value order of each block is unchanged after data embedding and the property guarantees the reversibility. In this work, instead of the difference between the maximum and second largest value of a block (or, the minimum and second smallest value of a block) considered in Li et al.ʼs method, new differences are computed and new histogram-modification-strategy is utilized. Take the maximum for example, the new difference is defined considering the pixel locations of the maximum and second largest value. In this way, the blocks where the maximum equals to the second largest value can be exploited to embed data while these blocks suitable for RDH are not utilized in Li et al.ʼs work. This can better exploit image redundancy and achieve a superior embedding performance. Extensive experiments verify that the proposed method outperforms Li et al.ʼs and some other state-of-the-art works.     

Adaptive reversible watermarking with improved embedding capacity

Embedding capacity is one of the most important issues of the reversible watermarking. However, the theoretical maximum embedding capacity of most reversible watermarking algorithms is only 1.0 bits per pixel (bpp). To achieve a higher capacity, we have to modify the least significant bit (LSB) multiple times which definitely lowers the quality of the embedded image. To this end, this paper proposes a novel reversible watermarking algorithm by employing histogram shifting and adaptive embedding. Specifically, the amount of the embedded watermark is adaptively determined in terms of the context of each pixel. For pixels with small prediction error, we modify the second, third and even the fourth LSBs as well to embed more than one watermark bit. Consequently, the proposed method achieves the embedding capacity larger than 1.0 bpp in single-pass embedding as well as bringing relatively low embedding distortion. The superiority of the proposed method is experimental verified by comparing with other existing schemes.     

基于预测误差差值扩展和最低有效位替换的可逆数据隐藏

将差值扩展技术应用于彩色图像,提出一种基于预测误差差值扩展和最低有效位（LSB）替换的彩色图像可逆数据隐藏算法。针对传统差值扩展技术存在过分修改像素灰度值、定位图偏大等缺点,首先利用色彩分量间的相关性减小差值,并将差值扩展量分散到两个色彩分量中;其次,改变差值扩展公式以减少不可扩展差值的数量,提高定位图的压缩率,从而增加嵌入容量;最后,运用LSB替换法嵌入数据,将差值扩展与数据嵌入过程分离,嵌入端和提取端均只需进行一次差值扩展,嵌入和提取效率得以提高。提取端在提取信息时可根据需要无损地恢复原始图像。实验结果表明,该算法在提高嵌入容量和图像质量的同时降低了算法复杂度。